Building a Data Warehouse

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Most developers are scared of “Business Intelligence” or BI. Most think that BI consists of cubes, pivot/drill down apps, and analytical decision support systems. While those are very typical outcomes of a BI effort, many people forget about the first step, the data warehouse.

Typically this is what happens with a BI effort. A system is built, usually a system that deals with transactions. We call this an OLTP or on-line transaction processing system. Some time passes and reports are bolted on and some business analysts build some pivot tables from “raw dumps” of data. As the system grows, reports start to slow since the system is optimized to deal with one record at a time. Someone, usually a CTO type says: “we need a BI system.” A development effort is then spent to build a data warehouse and cubes, and some kind of analytical system on top of those cubes.

  • Part I: When to build your data warehouse
  • Part II: Building a new schema
  • Part III: Location of your data warehouse
  • Part IV: Extraction, Transformation, and Load
  • Part V: Application Development Options
  • Tags: introduction, excel


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